Datasets:

jzpeng
/

devikaskumar_test_v4l2_fix

license: apache-2.0
task_categories:
  - robotics
tags:
  - tsfile
  - timeseries
  - tabular
  - lerobot
modality:
  - timeseries
  - tabular
pretty_name: devikaskumar test_v4l2_fix TsFile
size_categories:
  - 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/devikaskumar_test_v4l2_fix.tsfile

devikaskumar/test_v4l2_fix (TsFile)

This repository is an Apache TsFile conversion of the LeRobot dataset devikaskumar/test_v4l2_fix.

Modalities: Time-series, tabular.

Source dataset

Author: devikaskumar
License: Apache-2.0
Robot type: so101_follower
LeRobot codebase: v2.1
Task: test (one task, task_index=0)
Split: train (0:52 in the source metadata)
Scale: 52 episodes, 15,702 frames, one chunk, 30 fps
Source frame files: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet

The original dataset contains 104 camera videos (two streams per episode). The videos are not copied into this TsFile dataset. They remain available in the source repository under videos/, with files at videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4. The two source video features are observation.images.webcam and observation.images.realsense; both are 480×640 RGB, AV1, 30 fps, with no audio.

Converted files

TsFile: data/devikaskumar_test_v4l2_fix.tsfile
Table: devikaskumar_test_v4l2_fix
Rows: 15,702
Devices: 52 episode/task tag combinations
TsFile size: approximately 386 KB (the source Parquet shards total approximately 913 KB)
Metadata: meta/ is retained from the source; meta/info.json describes the converted TsFile and records the source/video mapping in tsfile_conversion.

Schema

Time is round(timestamp * 1000) in milliseconds and restarts at zero for each episode. The redundant source timestamp field is dropped.

TAG columns (the TsFile table/device dimensions):

episode_index (INT64 source value, stored as a TAG)
task_index (INT64 source value, stored as a TAG)

FIELD columns:

frame_index (INT64)
sample_index (INT64), renamed from source index
action_0 … action_5 (FLOAT), flattened from action[6]
observation_state_0 … observation_state_5 (FLOAT), flattened from observation.state[6] (. becomes _)

Conversion and compression

The generic LeRobot converter was run in merged mode, so all source episode shards are stored in one table-model TsFile. Query an episode by filtering the episode_index and task_index TAG columns. Numeric encoding follows the compact profile requested for this conversion: FLOAT/DOUBLE use GORILLA, INT32/INT64 and Time use TS_2DIFF, and physical columns use LZ4.

No source rows or numeric fields are intentionally removed except the redundant timestamp field. The video fields are omitted from TsFile because videos are external binary streams; their source paths and frame alignment metadata are recorded in meta/info.json.

Validation

The generated TsFile was opened and queried with the Apache TsFile Python SDK. The authoritative TsFile metadata row count and staged Parquet row count both equal 15,702; query readback also returned 15,702 rows across 52 devices.

Usage

from tsfile import TsFileReader

path = "data/devikaskumar_test_v4l2_fix.tsfile"
reader = TsFileReader(path)
table = reader.get_all_table_schemas()["devikaskumar_test_v4l2_fix"]
columns = [
    c.get_column_name()
    for c in table.get_columns()
    if c.get_column_name() != "Time"
]

with reader.query_table(
    "devikaskumar_test_v4l2_fix", columns, batch_size=65536
) as result:
    batch = result.read_arrow_batch()